Beispiel #1
0
def plot_one_boxplot_r(values, main="", logstring=""):
    from rpy import r
    if values.ndim == 1:
        v = resize(values, (1, values.size))
    else:
        v = values
    r.boxplot(v[0,:], xlim=[0,v.shape[0]+1], ylim=r.c(values.min(), values.max()), range=0, log=logstring,
              main=main)
    for i in range(1, v.shape[0]):
        r.boxplot(v[i,:], at=i, add=True, range=0, log=logstring)
Beispiel #2
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def create_p_value_boxplot_eps(best_p_values, filename):
    from rpy import r
    r.postscript(filename, horizontal=False, height=4.5, width=6, pointsize=10)
    try:
        keys = best_p_values.keys()
        keys.sort()
        r.boxplot(
            map(best_p_values.get, keys), 
            names=map(str, keys),
            xlab="sample size", ylab="p-score")
    finally:
        r.dev_off()
Beispiel #3
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def create_p_value_boxplot_eps(best_p_values, filename):
    from rpy import r
    r.postscript(filename, horizontal=False, height=4.5, width=6, pointsize=10)
    try:
        keys = best_p_values.keys()
        keys.sort()
        r.boxplot(map(best_p_values.get, keys),
                  names=map(str, keys),
                  xlab="sample size",
                  ylab="p-score")
    finally:
        r.dev_off()
Beispiel #4
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def plots(regression_o, getData_o):
    """Plots the dataset with a regression line and a boxplot using R."""
    fname1 = 'car_regress.pdf'
    r.pdf(fname1)
    r.plot(getData_o, ylab='dist', xlab='speed')
    r.abline(regression_o['(Intercept)'], regression_o['y'], col='red')
    r.dev_off()

    fname2 = 'car_hist.pdf'
    r.pdf(fname2)
    r.boxplot(getData_o, names=['dist', 'speed'])
    r.dev_off()

    return fname1, fname2